Location: Crop Production Systems ResearchTitle: Agri-BIGDATA: A smart pathway for crop nitrogen inputs
|YANG, GUIJUN - National Engineering Research Center For Information Technology In Agriculture|
|ZHAO, CHUNJIANG - National Engineering Research Center For Information Technology In Agriculture|
Submitted to: Artificial Intelligence in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/4/2020
Publication Date: 8/8/2020
Citation: Yang, G., Huang, Y., Zhao, C. 2020. Agri-BIGDATA: A smart pathway for crop nitrogen inputs. Trends in Plant Science. 4:150-152.
Interpretive Summary: Reduction of crop inputs is required for new sustainable agronomic practices and environmental conservation. Recently, scientists at the University of Cambridge, UK have introduced strategic plans for reducing crop nitrogen inputs in sustainable programs. Scientists at the National Engineering Research Center for Information Technology for Agriculture, Bejing, China, and USDA, ARS, Crop Production Systems Research Unit, Stoneville, Mississippi, investigated the role of big data for agricultural uses and introduced an integrated and comprehensive agricultural Big Data (Agri-BigData) framework that lowers the crop nitrogen requirement to levels below that suggested by the UK scientists. The Agri-BigData framework uses information from sensors, drones, and meteorological and soil databases, creating smart agriculture for the next decade in sustainable agricultural systems.
Technical Abstract: It is important to formulate strategic plans for reducing crop nitrogen inputs in sustainable systems. Scientists at the University of Cambridge, UK introduced strategic plans for reducing crop nitrogen inputs via joint efforts of farmers, breeders and scientists, while sustaining cereal yields and reducing greenhouse gas emissions. For this study, we investigate and discuss the role of big data by introducing an integrated and comprehensive agricultural Big Data (Agri-BigData) framework. It lowers the crop production nitrogen requirement beyond that suggested by the UK scientists, both in the first level collaborative work among geneticists, breeders, agronomists and plant scientists, and when providing effective guidance for variety selection and cultivation practices based on the Agri-BigData framework. Our framework consists of genotype-phenotype association studies with variety traits, cultivation devices equipped with sensors, unmanned aerial vehicles, remote sensing observations, and meteorological and soil databases. The applications and practices of Agri-Big Data are creating a new era of ‘smart farming’ for the world to behold.